# Channel flow around a cylinder at Mach 3
#
# Boundary conditions are supersonic Mach 3 inflow at the left portion of the domain
# and supersonic outflow at the right portion of the domain. The top and bottom of the
# channel as well as the cylinder are treated as Euler slip wall boundaries.
# This flow results in strong shock reflections / interactions as well as Kelvin-Helmholtz
# instabilities at later times as two Mach stems form above and below the cylinder.
#
# For complete details on the problem setup see Section 5.7 of the paper:
# - Jean-Luc Guermond, Murtazo Nazarov, Bojan Popov, and Ignacio Tomas (2018)
#   Second-Order Invariant Domain Preserving Approximation of the Euler Equations using Convex Limiting.
#   [DOI: 10.1137/17M1149961](https://doi.org/10.1137/17M1149961)
#
# Keywords: supersonic flow, shock capturing, AMR, unstructured curved mesh, positivity preservation, compressible Euler, 2D

using OrdinaryDiffEqSSPRK
using Trixi

###############################################################################
# semidiscretization of the compressible Euler equations

equations = CompressibleEulerEquations2D(1.4)

@inline function initial_condition_mach3_flow(x, t, equations::CompressibleEulerEquations2D)
    # set the freestream flow parameters
    rho_freestream = 1.4
    v1 = 3.0
    v2 = 0.0
    p_freestream = 1.0

    prim = SVector(rho_freestream, v1, v2, p_freestream)
    return prim2cons(prim, equations)
end

initial_condition = initial_condition_mach3_flow

# Supersonic inflow boundary condition.
# Calculate the boundary flux entirely from the external solution state, i.e., set
# external solution state values for everything entering the domain.
@inline function boundary_condition_supersonic_inflow(u_inner,
                                                      normal_direction::AbstractVector,
                                                      x, t, surface_flux_function,
                                                      equations::CompressibleEulerEquations2D)
    u_boundary = initial_condition_mach3_flow(x, t, equations)
    return flux(u_boundary, normal_direction, equations)
end

# Supersonic outflow boundary condition.
# Calculate the boundary flux entirely from the internal solution state. Analogous to supersonic inflow
# except all the solution state values are set from the internal solution as everything leaves the domain
@inline function boundary_condition_outflow(u_inner, normal_direction::AbstractVector, x, t,
                                            surface_flux_function,
                                            equations::CompressibleEulerEquations2D)
    return flux(u_inner, normal_direction, equations)
end

boundary_conditions = (; Bottom = boundary_condition_slip_wall,
                       Circle = boundary_condition_slip_wall,
                       Top = boundary_condition_slip_wall,
                       Right = boundary_condition_outflow,
                       Left = boundary_condition_supersonic_inflow)

volume_flux = flux_ranocha_turbo
# Up to version 0.13.0, `max_abs_speed_naive` was used as the default wave speed estimate of
# `const flux_lax_friedrichs = FluxLaxFriedrichs(), i.e., `FluxLaxFriedrichs(max_abs_speed = max_abs_speed_naive)`.
# In the `StepsizeCallback`, though, the less diffusive `max_abs_speeds` is employed which is consistent with `max_abs_speed`.
# Thus, we exchanged in PR#2458 the default wave speed used in the LLF flux to `max_abs_speed`.
# To ensure that every example still runs we specify explicitly `FluxLaxFriedrichs(max_abs_speed_naive)`.
# We remark, however, that the now default `max_abs_speed` is in general recommended due to compliance with the
# `StepsizeCallback` (CFL-Condition) and less diffusion.
surface_flux = FluxLaxFriedrichs(max_abs_speed_naive)

polydeg = 3
basis = LobattoLegendreBasis(polydeg)
shock_indicator = IndicatorHennemannGassner(equations, basis,
                                            alpha_max = 0.5,
                                            alpha_min = 0.001,
                                            alpha_smooth = true,
                                            variable = density_pressure)
volume_integral = VolumeIntegralShockCapturingHG(shock_indicator;
                                                 volume_flux_dg = volume_flux,
                                                 volume_flux_fv = surface_flux)
solver = DGSEM(polydeg = polydeg, surface_flux = surface_flux,
               volume_integral = volume_integral)

# Get the unstructured quad mesh from a file (downloads the file if not available locally)
mesh_file = Trixi.download("https://gist.githubusercontent.com/andrewwinters5000/a08f78f6b185b63c3baeff911a63f628/raw/addac716ea0541f588b9d2bd3f92f643eb27b88f/abaqus_cylinder_in_channel.inp",
                           joinpath(@__DIR__, "abaqus_cylinder_in_channel.inp"))

mesh = P4estMesh{2}(mesh_file)

semi = SemidiscretizationHyperbolic(mesh, equations, initial_condition, solver;
                                    boundary_conditions = boundary_conditions)

###############################################################################
# ODE solvers

tspan = (0.0, 2.0)
ode = semidiscretize(semi, tspan)

# Callbacks

summary_callback = SummaryCallback()

analysis_interval = 1000
analysis_callback = AnalysisCallback(semi, interval = analysis_interval)

alive_callback = AliveCallback(analysis_interval = analysis_interval)

save_solution = SaveSolutionCallback(interval = 1000,
                                     save_initial_solution = true,
                                     save_final_solution = true,
                                     solution_variables = cons2prim)

# positivity limiter necessary for this example with strong shocks. Very sensitive
# to the order of the limiter variables, pressure must come first.
positivity_limiter = PositivityPreservingLimiterZhangShu(thresholds = (5.0e-7, 1.0e-6),
                                                         variables = (pressure,
                                                                      Trixi.density))

amr_indicator = IndicatorLöhner(semi, variable = Trixi.density)

amr_controller = ControllerThreeLevel(semi, amr_indicator,
                                      base_level = 0,
                                      med_level = 3, med_threshold = 0.05,
                                      max_level = 5, max_threshold = 0.1)

# Set `limiter! = positivity_limiter` to apply the positivity-preserving limiter after 
# coarsening and refinement steps.
amr_callback = AMRCallback(semi, amr_controller,
                           interval = 1,
                           adapt_initial_condition = true,
                           adapt_initial_condition_only_refine = true,
                           limiter! = positivity_limiter)

callbacks = CallbackSet(summary_callback,
                        analysis_callback, alive_callback,
                        save_solution,
                        amr_callback)

###############################################################################
# run the simulation
sol = solve(ode, SSPRK43(; stage_limiter! = positivity_limiter);
            ode_default_options()..., callback = callbacks);
